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Sensors 2019, 19(2), 423; https://doi.org/10.3390/s19020423

Spatio-Temporal Features in Action Recognition Using 3D Skeletal Joints

Faculty of Automatic Control and Computers, University Politehnica Bucharest, București 060042, Romania
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Received: 26 October 2018 / Revised: 14 January 2019 / Accepted: 17 January 2019 / Published: 21 January 2019
(This article belongs to the Section Internet of Things)
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Abstract

Robust action recognition methods lie at the cornerstone of Ambient Assisted Living (AAL) systems employing optical devices. Using 3D skeleton joints extracted from depth images taken with time-of-flight (ToF) cameras has been a popular solution for accomplishing these tasks. Though seemingly scarce in terms of information availability compared to its RGB or depth image counterparts, the skeletal representation has proven to be effective in the task of action recognition. This paper explores different interpretations of both the spatial and the temporal dimensions of a sequence of frames describing an action. We show that rather intuitive approaches, often borrowed from other computer vision tasks, can improve accuracy. We report results based on these modifications and propose an architecture that uses temporal convolutions with results comparable to the state of the art. View Full-Text
Keywords: action recognition; AmI; AAL action recognition; AmI; AAL
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
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Trăscău, M.; Nan, M.; Florea, A.M. Spatio-Temporal Features in Action Recognition Using 3D Skeletal Joints. Sensors 2019, 19, 423.

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